I-Corps: Network-based artificial intelligence (AI) model that will enable rapid and detailed diagnosis and treatment recommendations for advanced cardiac disease patients

I-Corps:基于网络的人工智能(AI)模型,将为晚期心脏病患者提供快速、详细的诊断和治疗建议

基本信息

  • 批准号:
    2120858
  • 负责人:
  • 金额:
    $ 5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-02-15 至 2022-07-31
  • 项目状态:
    已结题

项目摘要

The broader impact/commercial potential of this I-Corps project is the development of digital interventions to detect and deliver early treatment recommendations for advanced cardiac disease. Through the use of artificial intelligence, it is possible address one of the most pressing healthcare burdens in the United States by detecting trajectories of chronic heart disease early. As a result, this technology would enable multiple applications including, but not limited to, reductions in healthcare-related costs, chronic disease burden, specialist care gaps, and time to treatment. This proposed technology may deliver a new era of software as a digital therapeutic, an area traditionally reserved for non-chronic conditions. This I-Corps project is based on the development of a software platform using neural network models that leverage the use of biomarkers coupled with clinical vitals. Combining molecular and clinical data applied through natural experimentation, has made it is possible to understand the state changes of heart disease. Through the use of deep neural network learning, the proposed project goal is to make algorithms think and understand as humans by replicating the human brain connection and focusing on learning state changes rather than task-specific algorithms. Previous work on molecular profiling paired with clinical data within the realm of heart transplantation has yielded promising results in creating new sub-diagnosis as well as new artificial intelligence-guided therapy optimization protocols.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
I-Corps项目更广泛的影响/商业潜力是开发数字干预措施,以检测和提供晚期心脏病的早期治疗建议。通过使用人工智能,有可能通过早期检测慢性心脏病的轨迹来解决美国最紧迫的医疗负担之一。因此,这项技术将实现多种应用,包括但不限于减少与医疗保健相关的成本、慢性病负担、专科护理差距和治疗时间。这项提议的技术可能会带来一个新的软件时代,作为数字治疗,一个传统上为非慢性疾病保留的领域。I-Corps项目基于一个软件平台的开发,该平台使用神经网络模型,利用生物标志物与临床生命体征相结合。通过自然实验应用分子与临床数据相结合,使了解心脏病的状态变化成为可能。通过使用深度神经网络学习,提出的项目目标是通过复制人类大脑连接并专注于学习状态变化而不是特定任务的算法,使算法像人类一样思考和理解。先前在心脏移植领域的分子谱分析与临床数据配对的工作在创建新的亚诊断以及新的人工智能引导的治疗优化方案方面取得了有希望的结果。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Martin Cadeiras其他文献

Remote Monitoring Titration Clinic To Implement Guideline-directed Medical Therapy For Heart Failure Patients With Reduced Ejection Fraction: A Pilot Intervention Study
  • DOI:
    10.1016/j.cardfail.2023.10.087
  • 发表时间:
    2024-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Erick Romero;Stella Yala;Camryn Sellers-Porter;David Liem;Julie Bidwell;Imo Ebong;Michael Gibson;Martin Cadeiras
  • 通讯作者:
    Martin Cadeiras
INFLUENCE OF PRE-TRANSPLANT CHRONIC KIDNEY DISEASE ON OUTCOMES OF ADULT HEART TRANSPLANT-ONLY RECIPIENTS: UNOS REGISTRY ANALYSIS
  • DOI:
    10.1016/s0735-1097(13)60793-7
  • 发表时间:
    2013-03-12
  • 期刊:
  • 影响因子:
  • 作者:
    Eugene Christopher DePasquale;Richard Cheng;Mrudula Allareddy;Arnold Baas;Martin Cadeiras;Daniel Cruz;Tam Khuu;Ali Nsair;Daniel Jacoby;Mario Deng
  • 通讯作者:
    Mario Deng
CARDIAC RETRANSPLANTATION: HOW FAR HAVE WE COME?
  • DOI:
    10.1016/s0735-1097(14)60807-x
  • 发表时间:
    2014-04-01
  • 期刊:
  • 影响因子:
  • 作者:
    Eugene Christopher DePasquale;Richard Cheng;Ali Nsair;Leigh Reardon;Arnold Baas;Martin Cadeiras;Daniel Cruz;Nancy Halnon;Juan Alejos;Mario Deng;Hillel Laks;Abbas Ardehali
  • 通讯作者:
    Abbas Ardehali
P22-052-23 Implementation and Effectiveness of the DASH Diet for Outpatient Heart Failure Management: Study Protocol and Challenges of a Pilot Pragmatic Clinical Trial
  • DOI:
    10.1016/j.cdnut.2023.101755
  • 发表时间:
    2023-07-01
  • 期刊:
  • 影响因子:
  • 作者:
    Brooke Wickman;Camryn Sellers-Porter;Martin Cadeiras;Frederick Meyers;Francene Steinberg
  • 通讯作者:
    Francene Steinberg
Novel Echocardiographic Parameters For Predicting Clinical Outcomes In Transthyretin Amyloid Cardiomyopathy
  • DOI:
    10.1016/j.cardfail.2023.10.406
  • 发表时间:
    2024-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yeabsra Aleligne;Martin Cadeiras;Michael Gibson;Shirin Jimenez;David Liem;Julie Bidwell;Imo Ebong
  • 通讯作者:
    Imo Ebong

Martin Cadeiras的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似国自然基金

多维在线跨语言Calling Network建模及其在可信国家电子税务软件中的实证应用
  • 批准号:
    91418205
  • 批准年份:
    2014
  • 资助金额:
    170.0 万元
  • 项目类别:
    重大研究计划
基于Wireless Mesh Network的分布式操作系统研究
  • 批准号:
    60673142
  • 批准年份:
    2006
  • 资助金额:
    27.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: SHF: Small: Efficient and Scalable Privacy-Preserving Neural Network Inference based on Ciphertext-Ciphertext Fully Homomorphic Encryption
合作研究:SHF:小型:基于密文-密文全同态加密的高效、可扩展的隐私保护神经网络推理
  • 批准号:
    2412357
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
A Knowledge-aware Multi-tasks-based Disease Network Construction on Biomedical Literature
基于生物医学文献的知识感知多任务疾病网络构建
  • 批准号:
    24K15097
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
EEG Based Global Network Models and Platform for Brain States Assessment
基于脑电图的大脑状态评估全球网络模型和平台
  • 批准号:
    DP240102329
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Discovery Projects
Heterogeneous Graph Neural Network based Federated Mobile Crowdsensing
基于异构图神经网络的联合移动群智感知
  • 批准号:
    23K24829
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Development of data-driven multiple sound spot synthesis technology based on deep generative neural network models
基于深度生成神经网络模型的数据驱动多声点合成技术开发
  • 批准号:
    23K11177
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
CSR: Small: Processing-in-Memory enabled Manycore Systems to Accelerate Graph Neural Network-based Data Analytics
CSR:小型:启用内存处理的众核系统可加速基于图神经网络的数据分析
  • 批准号:
    2308530
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
NICHD Neonatal Research Network (NRN): Clinical Centers (UG1 Clinical Trial Optional
NICHD 新生儿研究网络 (NRN):临床中心(UG1 临床试验可选
  • 批准号:
    10682888
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Music4Pain Network: A research network to advance the study of mechanisms underlying the effects of music and music-based interventions on pain.
Music4Pain Network:一个研究网络,旨在推进音乐和基于音乐的疼痛干预措施的影响机制的研究。
  • 批准号:
    10764417
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Network Canvas 2.0: Enhancing network data capture for drug use and HIV research
Network Canvas 2.0:增强药物使用和艾滋病毒研究的网络数据捕获
  • 批准号:
    10715902
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
NIDA Clinical Trials Network: New York Node
NIDA 临床试验网络:纽约节点
  • 批准号:
    10855627
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了